臺灣博碩士論文加值系統

研究目的：了解臺灣臨床護理人員工作壓力現況，分析不同科別的臨床護理人員工作壓力源差異，並比較不同科別臨床護理人員的心理健康程度差異。

研究方法：本研究以衛生福利部2010-2013年「新制醫院評鑑合格之醫院(含精神科) 」為抽樣母群體，以內政部之全國北中南東分區，以系統抽樣方式於各區抽取有執業登記之全職臨床護理人員，以郵寄方式進行問卷發放。收案對象包含：一般病房、產兒科病房、急性精神病房、慢性精神病房、加護病房、門診、手術室、急診、血液透析室、呼吸照護中心與其他工作科別之護理人員。問卷內容包括：護理工作壓力源量表、職場疲勞量表、簡式健康量表與個人基本資料等四大部份，並以JMP10.0統計軟體進行分析。由描述性統計呈現個人資料變項、護理工作壓力源、心理健康狀態、自覺工作壓力表現與離職傾向的分布情形，再以羅吉斯迴歸(logistic regression)分析臨床護理人員的離職傾向相關因素。

研究結果：本研究共回收1,867份有效問卷(回收率79.3%)。參與研究的護理人員平均年齡為33.5歲(標準差7.4)，平均目前工作年資為7.6年(標準差6.4)，平均臨床護理工作總年資為10.9(標準差7.3)。近三個月主要工作班別為白班，工作單位屬8小時班制者，平均每日工作時數8.7小時，平均一週工作45.2小時；工作單位屬12小時班制者，平均每日工作12.4小時，平均一週工作57.3小時。護理工作壓力源量表總分平均值為61.7(標準差14.1)，以工作科別分析量表各題時，得不同科別之主要工作壓力源相異，又以「須承受病人或家屬的負向情緒」、「醫師的情緒性言語」、「因工作責任，須改變家庭活動安排」、「須支援其他專科病房」、「同事間沒有良好的互動關係」以及「病人可能有感染性疾病(如SARS，AIDS等)」為多數科別平均值達3分以上的工作壓力源，且多屬於「職業危害」分量表之題項。參與研究的護理人員中，僅4.2%身心狀況適應良好，34.3%有輕度心理困擾，24.4%有中度心理困擾，7.1%為重度心理困擾。

結論與建議：護理工作壓力源量表總分屬於前20%(≧72分)者，於自覺壓力表現的預測模式中，發生高個人疲勞、高對服務對象疲勞、有心理困擾、常自覺壓力大、工作滿意度差的機率，以及離職意圖遠高於非前20%者。護理工作壓力源因工作科別不同而有差異。一般病房顯著的護理工作壓力源多與職業危害及負荷過重有關；急診獨特的護理工作壓力源則為「工作時遭遇心理暴力」。護理人員的心理困擾程度因工作科別不同而有所差異，建議醫療院所可定期使用護理工作壓力源量表評估工作壓力程度與分析護理工作壓力源，作為改善職業環境的參考。

Objective: The purpose of this study was to investigate general occupational stress in nurses, and variation of occupational stressors and mental health status among nurses working in different hospital units.

Methods: The study population was all qualified hospitals of New Hospital Accreditation between 2010 and 2013. A cross-sectional questionnaire survey using systematic sampling method was performed in North, Central, South and East Taiwan. Questionnaires were delivered to the study hospitals units including general wards, gynecology and pediatric wards, acute psychiatric wards, chronic psychiatric wards, intensive care units, outpatient department, operating room, emergency department, dialysis center, respiratory care unit and others. The questionnaires include the Nurse Occupational Stressor Scale (NOSS), occupational burnout inventory, Brief Symptom Rating Scale (BSRS-5) and demographics. The JMP version 10.0 statistical software was used for data analysis. Descriptive statistics include demographics, distribution of nursing occupational stressors, mental health status, expressions of occupational stress and intention to leave. Logistic regression was used to identify the predictive factors for nurses’ intention to leave their jobs.

Results: A total of 1,867 questionnaires were eligible for final analysis, resulted a high response rate of 79.3%. The mean age was 33.5 years (SD 7.4), and the average work tenure was 10.9 years (SD 7.3). The average working hour per day was 8.7 hours and 45.2 hours per week in 8-hour shifts. In 12- hour shifts, the average working hour per day and per week were 12.4 hours and 57.3 hours. The mean NOSS score was 61.7 (SD 4.1). The major occupational stressors were different across units. “having to bear negative sentiments of patients and/or of their relatives,” “emotional wording of physicians,” “compulsory alteration of family activities due to work responsibilities,” “having to be a substitute for other specialized units,” “poor workplace relationships with colleagues,” and “the patient might have contagious disease, such as SARS and AIDS” were the most common occupational stressors, and of which were classified as “Occupational Hazards” subscale of NOSS. Of all participants, 4.2% self-reported to be in good health, while 34.3% reported to have minor mental disorders associated with depression and anxiety, and 7.1% in severe condition.

Conclusions and Recommendations: Nurses with mean NOSS score of 20% tile (≧72) were more likely to have personal burnout, client burnout, psychiatric morbidity, stress, job dissatisfaction, and intention to leave. The nursing occupational stressors were different across hospital units. The significant stressors of general wards were associated with occupational hazards and workload. The unique stressor of emergency department was “psychosocial harassment at work”. In summary, mental health status of nurses were different across hospital units, periodically identify nursing stressors using NOSS and to to improve working environment for nurses are warranted.

目錄
口試委員審定書 i
誌謝 ii
摘要 iii
Abstract v
目錄 vii
圖目錄 ix
表目錄 x
第一章 緒論 1
第一節 研究背景與動機 1
第二章 文獻查證 3
第一節 護理工作壓力源 3
第二節 不同科別之臨床護理人員工作壓力概況 6
第三節 護理工作壓力源量表 8
第三章 研究目的 10
第四章 研究方法 11
第一節 研究架構 11
第二節 研究設計 11
第三節 研究場所及對象 12
第四節 研究工具 14
第五節 資料收集過程 15
第六節 資料統計與分析 16
第五章 研究結果 17
第一節 個人基本資料與工作狀態之分布 18
第二節 護理工作壓力源調查結果 25
第三節 自覺壓力表現及壓力相關因素 42
第四節 離職意圖及離職相關因素 68
第六章 討論 77
第一節 護理工作壓力概況 77
第二節 護理工作壓力源 79
第三節 護理人員之心理健康程度 83
第四節 預測離職相關因素探討 85
第五節 研究限制 86
第七章 研究結論與建議 87
第一節 結論 87
第二節 建議 88
參考文獻 89
附錄一 護理工作壓力源量表與心理健康調查問卷 99

圖目錄
圖 1 研究架構 11
圖 2 有效問卷選取流程圖 17
圖 3 班別與工作科別平均護病比 23
圖 4 醫院層級與工作科別之白班平均護病比 23
圖 5 醫院層級與工作科別之小夜班平均護病比 24
圖 6 醫院層級與工作科別之大夜班平均護病比 24
圖 7「職業危害」分量表各題項之「很同意」與「同意」比率圖 28
圖 8「工作生活衝突」分量表各題項之「很同意」與「同意」比率圖 30
圖 9「負荷過重」分量表各題項之「很同意」與「同意」比率圖 32
圖 10「人力短缺」分量表各題項之「很同意」與「同意」比率圖 34
圖 11「個人疲勞」分量表各題項之「總是」與「常常」比率圖 42
圖 12「對服務對象疲勞」分量表各題項之「總是」與「常常」比率圖 46
圖 13自覺健康狀況 51
圖 14自覺工作壓力比率 58
圖 15工作滿意度比率 59
圖 16預測高個人疲勞模式之ROC曲線(AUC=0.80) 62
圖 17預測高對服務對象疲勞模式之ROC曲線(AUC=0.74) 63
圖 18預測有心理困擾模式之ROC曲線(AUC=0.74) 64
圖 19預測常自覺工作壓力大模式之ROC曲線(AUC=0.74) 65
圖 20預測工作滿意度差模式之ROC曲線(AUC=0.75) 67
圖 21離職分數 68
圖 22以高強度護理工作壓力源預測離職傾向之ROC曲線(AUC=0.79) 70
圖 23以自覺壓力表現預測離職傾向之ROC曲線(AUC=0.87) 72

表目錄
表 1全國各區域抽樣及回收情形 12
表 2全國各醫院類別抽樣及回收情形 13
表 3研究對象個人資料與工作狀態分布(N=1,867) 19
表 4工作班別分布(N=1,867) 21
表 5工作與睡眠時間(N=1,867) 21
表 6護理工作壓力源量表平均值與標準差分布情形(N=1,867) 25
表 7各科別於「職業危害」分量表各題項之「很同意」與「同意」比率分布 29
表 8各科別於「工作生活衝突」分量表各題項之「很同意」與「同意」比率分布 31
表 9各科別於「負荷過重」分量表各題項之「很同意」與「同意」比率分布 33
表 10各科別於「人力短缺」分量表各題項之「很同意」與「同意」比率分布 34
表 11各科別於護理工作壓力源量表其他題項之「很同意」與「同意」比率分布 36
表 12不同工作科別之護理工作壓力源得分 39
表 13個人疲勞量表平均值與標準差分布情形(N=1,867) 43
表 14各科別於「個人疲勞」分量表各題項之「總是」與「常常」比率分布 45
表 15對服務對象疲勞量表平均值與標準差分布情形(N=1,867) 47
表 16各科別於「對服務對象疲勞」分量表各題項之「總是」與「常常」比率分布 50
表 17研究對象心理困擾分布情形(N=1,867) 52
表 18不同工作科別之心理困擾程度 55
表 19研究對象自殺意念分布情形(N=1,866) 56
表 20高個人疲勞之預測模式 61
表 21高對服務對象疲勞之預測模式 62
表 22有心理困擾之預測模式 64
表 23常自覺工作壓力大之預測模式 65
表 24工作滿意度差之預測模式 66
表 25以高強度護理工作壓力源預測離職傾向之預測模式 69
表 26以自覺壓力預測離職傾向之預測模式 71
表 27一般病房護理工作壓力源與自覺壓力表現及離職傾向之羅吉斯迴歸分析：控制個人變項與職場特質(N=564) 74

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